xinqiao123

xinqiao123's Stars

• azl397985856/leetcode

  LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)

  Language:JavaScript54.7k1.3k2579.5k

• diff-usion/Awesome-Diffusion-Models

  A collection of resources and papers on Diffusion Models

  Language:HTML11k26948945

• billryan/resume

  An elegant \LaTeX\ résumé template. 大陆镜像 https://gods.coding.net/p/resume/git

  Language:TeX9.3k84642.6k

• satellite-image-deep-learning/techniques

  Techniques for deep learning with satellite & aerial imagery

  8.7k278231.5k

• pengsida/learning_research

  本人的科研经验

  5.9k7228346

• guanyingc/latex_paper_writing_tips

  Tips for Writing a Research Paper using LaTeX

  Language:TeX3k240358

• microsoft/torchgeo

  TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

  Language:Python2.7k51441341

• ddz16/TSFpaper

  This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the type of model.

  2k6523180

• JavierAntoran/Bayesian-Neural-Networks

  Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

  Language:Jupyter Notebook1.8k2724302

• MinZHANG-WHU/Change-Detection-Review

  A review of change detection methods, including codes and open data sets for deep learning. From paper: change detection based on artificial intelligence: state-of-the-art and challenges.

  834293183

• Linfeng-Tang/Image-Fusion

  Deep Learning-based Image Fusion: A Survey

  Language:MATLAB82099132

• chrieke/awesome-geospatial-companies

  :globe_with_meridians: List & Map of 700+ companies for geospatial jobs (GIS, Earth Observation, UAV, Satellite, Digital Farming, ..)

  Language:Python724324780

• PKUFlyingPig/UCB-CS70

  discrete mathematics and probability theory

  2132239

• aHuiWang/plot_demo

  论文里可以用到的实验图示例

  Language:Python2021154

• tom-andersson/icenet-paper

  Code associated with the paper 'Seasonal Arctic sea ice forecasting with probabilistic deep learning'

  Language:Python903819

• likyoo/Multimodal-Remote-Sensing-Toolkit

  A python tool to perform deep learning experiments on multimodal remote sensing data.

  Language:Python813512

• DeepAlchemy/DCIC22_SAR_ship_detection

  👁 2022年数字**创新大赛 (DCIC 2022) 卫星应用赛题——海上船舶智能检测第三名解决方案

  Language:Python500110

• zhengye1995/DCIC22-SAR-ship-detection

  DCIC22数字**22-海上船舶智能检测第二名方案

  Language:Python34114

• junkoda/kaggle_contrails_solution

  Solution for the Kaggle contrail segmentation competition

  Language:Jupyter Notebook25103

• SpaceNetChallenge/SAR-RGB-DataFusion

  A small codebase featuring a few elementary methods for SAR and Optical imagery data fusion

  Language:Jupyter Notebook25318

• ya0-sun/bboxRegNet4BldHeight

  Large-scale Building Height Retrieval from Single SAR Imagery based on Bounding Box Regression Networks

  Language:Python21114

• YonghaoXu/RSEN

  [IEEE TNNLS 2022] Robust Self-Ensembling Network for Hyperspectral Image Classification

  Language:Python19101

• astokholm/AI4ArcticSeaIceChallenge

  Language:Jupyter Notebook17107

• TeamEpochGithub/iv-q2-detect-kelp

  1st place solution of Team Epoch on the Kelp Wanted competition hosted on DrivenData.

  Language:Jupyter Notebook16311

• flateon/3DOC-SSAN-PyTorch

  A PyTorch implementation of paper: Hyperspectral Image Classification Based on 3-D Octave Convolution With Spatial–Spectral Attention Network (https://ieeexplore.ieee.org/document/9140029)

  Language:Python15100

• srxlnnu/BS2T

  BS2T: Bottleneck Spatial–Spectral Transformer for Hyperspectral Image Classification.

  Language:Python15202

• asylve/Sea-Ice

  Data science project producing sea ice concentration maps from satellite images.

  Language:Jupyter Notebook9102

• xultaeculcis/kelp-wanted-competition

  Estimating the extent of Giant Kelp Forests by segmenting Landsat imagery

  Language:Python6200

• asc-csa/Synthetic_Aperture_Radar_Tutorial

  🛰 Ce script didacticiel contient des exemples d’utilisation d’images de missions RADARSAT en python et QGIS pour aider les utilisateurs à utiliser les données CSA en fonction de leurs besoins. 🛰 This tutorial script contains samples for using RADARSAT missions images in python and QGIS to help users to make use of CSA data based on their needs.

  Language:Jupyter Notebook4212

• IoannisNasios/Kelp_Forests

  Segmenting Kelp Forests at Landsat images

  Language:Jupyter Notebook3100